Doowon Lee
Yonsei University · 工学
研究室紹介
Professor Doowon Lee's research lab specializes in the development of advanced 2D materials and resistive switching devices for next-generation sensing and neuromorphic computing applications. The lab focuses on creating high-performance, low-power gas sensors—particularly for NO and O₂—using memristor-based architectures (gasistors) and oxide semiconductors like MoS₂, SnO₂, and IGZO. A key research direction involves integrating these smart sensors with artificial intelligence, especially neural networks, to enable real-time, accurate, and energy-efficient environmental and biomedical monitoring. The lab also explores fundamental mechanisms in 2D materials and resistive switching for applications in label-free DNA detection and chiral separation.
Research Overview
Research Output Trend
Figures are computed from collected data and may differ slightly.
Selected Papers
15A field-effect transistor (FET) with two-dimensional (2D) few-layer MoS2 as a sensing-channel material was investigated for label-free electrical detection of the hybridization of deoxyribonucleic acid (DNA) molecules. The high-quality MoS2-channel pattern was selectively formedthrough the chemical reaction of the Mo layer with H2S gas. The MoS2 FET was very stable in an electrolyte and inert to pH changes due to the lack of oxygen-containing functionalities on the MoS2 surface. Hybridization of
We deal with a cost-based adaptive handover hysteresis scheme for the horizontal handover decision strategies, as one of the self-optimization techniques that can minimize the handover failure rate (HFR) in the 3rd generation partnership project (3GPP) long-term evolution (LTE) system based on the network-controlled hard handover. Especially, for real-time operation, we propose an adaptive hysteresis scheme with a simplified cost function considering some dominant factors closely related to HFR
Fast recovery, high sensitivity, high selectivity, and room temperature (RT) sensing characteristics of NO gas sensors are essential for environmental monitoring, artificial intelligence, and inflammatory diagnosis of asthma patients. However, the conventional semiconductor-type gas sensors have poor sensing characteristics that need to be solved, such as slow recovery speeds (>360 s), low sensitivity (3.8), and high operating temperatures (>300 °C). We propose here a memristor-based NO gas sens
Oxygen (O<sub>2</sub>) sensing in trace amounts and mixed gas is essential in many types of industries. Semiconductor sensors have proven to be invaluable tools for the O<sub>2</sub> measurements in a wide concentration range, but the sensors are only able to quantify O<sub>2</sub> in a concentration range of subppm, thus far, especially in mixed gas. We present in this paper a new concept for O<sub>2</sub> sensing with incomparable sensitivity using IGZO-films with oxygen vacancy-based conducti
Enantiomeric separations of six anionic and two neutral racemates were achieved using a fully substituted heptakis(6-hydroxyethylamino-6-deoxy)-beta-cyclodextrin (beta-CD-EA) as a chiral selector. As beta-CD-EA provides a dynamic coating on the capillary wall, reverse-polarity capillary electrophoresis (CE) configuration is applied for separations of anionic and neutral chiral compounds. Chiral separations of various classes of anionic and neutral enantiomers were found to be highly dependent on
Memristor-based gas sensors (gasistors) have been considered as the most promising candidate for detecting NO gas suitable for neural network (NN) analysis. In this work, in order to solve an overfitting issue arising from the training data when using a single gasistor, which degrades the accuracy of NN, we here propose a metal–insulator-silicon (MIS)-structured Zr 3 N 4 -based gasistor array that results in an improvement in both the accuracy of the NN analysis and the efficiency of the operati
In aerospace applications, SiOx deposition on perovskite solar cells makes them more stable. However, the reflectance of the light changes and the current density decreases can lower the efficiency of the solar cell. The thickness of the perovskite material, ETL, and HTL must be re-optimized, and testing the number of cases experimentally takes a long time and costs a lot of money. In this paper, an OPAL2 simulation was used to find the thickness and material of ETL and HTL that reduces the amou
Abstract—The expected low reliability of the silicon substrate at upcoming technology nodes presents a key challenge for digital system designers. Networks-on-chip (NoCs) are especially concerning because they are often the only communication infrastructure for the chips in which they are deployed. Recently, routing reconfiguration solutions have been proposed to address this problem. However, they come at a high silicon cost, and often require suspending the normal network activity while execut
Silicon devices are becoming less and less reliable as technology moves to smaller feature sizes. As a result, digital systems are increasingly likely to experience permanent failures during their life-time. To overcome this problem, networks-on-chip (NoCs) should be designed to, not only fulfill performance requirements, but also be robust to many fault occurrences. This paper proposes a fault- and application-aware routing framework called FATE: it leverages the diversity of communication patt